Your Virtual Cold Chain Assistant

Click on the country or more details


India                                       Nigeria

Funding. This project is funded by the MasterCard Center for Inclusive Growth, The Rockefeller Foundation, and giz.

Duration. 2 years (2021-2022 for India, 2021-2023 for Nigeria). 

CollaborationsBASE, Swiss Data Science Center, local service providers in India and Nigeria.

Contact. Thijs Defraeye (principal investigator).


Project background. 

Your virtual cold chain assistant aims to use open access, data-science-based mobile application to save food, improve food quality, reduce CO2 emissions, and enhance the livelihood of smallholder farmers in India. By leveraging available farm input data such as weather and precipitation data, historical hygrothermal data in storage, data on the farming system, and so on, this project will use machine learning coupled with physics-based modeling to provide smallholder farmers and service providers with real-time food quality metrics such as remaining shelf life, weight loss, microbial spoilage, etc. and pre-and post-harvest market analytics. With this information, farmers can make informed decisions on when and how to sell their produce. At the same time, this project will give the service providers access to sustainable, energy-efficient, clean, affordable, and easy to operate refrigeration systems.


Forecasting Fruit Freshness with Simulation Apps, September 2023, COMSOL, Link.

Onwude, D., Motmans, T., Shoji, K., Evangelista, R., Gajardo, J., Odion, D., Ikegwuonu, N., Adekanmbi, O., Hourri, S. and Defraeye, T., 2023. Bottlenecks in Nigeria's fresh food supply chain: What is the way forward?. Trends in Food Science & Technology. DOI

Odion, D., Shoji, K., Evangelista, R., Gajardo, J., Motmans, T., Defraeye, T. and Onwude, D., 2023. A GIS-based interactive map enabling data-driven decision-making in Nigeria's food supply chain. MethodsX, 10, p.102047. DOI

Li, D., Gajardo, J., Volpi, M. and Defraeye, T., 2023. Using machine learning to generate an open-access cropland map from satellite images time series in the indian himalayan region. Remote Sensing Applications: Society and Environment, p.101057. DOI

Knott, M., Perez-Cruz, F. and Defraeye, T., 2023. Facilitated machine learning for image-based fruit quality assessment. Journal of Food Engineering, 345, p.111401. DOI

You, L., Schudel, S. and Defraeye, T., 2023. Developing of biophysical food for monitoring postharvest supply chains for avocado and potato and deploying of biophysical apple. Journal of Food Engineering, 338, p.111219. DOI

Funding agency: